You don't need to be clairvoyant to see the future. By harnessing your customer data and predictive analytics, you have all the tools you need right in front of you. The good news is, you don't need to be a statistician or regression analyst to use predictive analytics either. With the help of your team, a few simple metric tools, or your local Orlando marketing agency, you can predict hundreds of business outcomes and behaviors that will inform your marketing efforts, so you and your team can work smarter, not harder.

With so many options to choose from, it can be difficult to narrow down the key metrics you want to predict. To begin, take a look at your sales or conversion funnel. Most industries have benchmarks for each step of the funnel. By comparing your demand generation movement, sign up rates, conversion rates, and retention rates to those averages, you can see where you're doing well and where you could use some help.

This quick needs assessment will help you focus your efforts and decide which data to hone in on first. As a rule, the following five metrics are a great place to start no matter how your business is performing.

1. Predictive analytics and customer lifetime value

Using the data from your conversion or sales rate and retention rate, you can predict the average lifespan, and thus the lifetime monetary value, of each customer or sale. As you invest in campaigns that turn prospects into customers, you can balance that return on investment (ROI) against what you predict those customers' lifetime value will be. If you're spending tons of money to acquire new customers, but their expected lifetime value is below that figure, it's time to take a new approach.

2. Churn, funnel efficiency, and cart abandonment

Although we often try to optimize for our sales, sometimes it is just as effective to optimize around our losses. If you can predict the risk of your customers defecting to your competition or leaving your site before they complete the sale, you can plan to close that gap through other initiatives. Your churn rate, funnel efficiency, and cart abandonment are all easily forecasted using simple analytics tools such as Google Analytics or Adobe Analytics and will help you understand what types of retention or conversion initiatives will be most profitable.

3. Purchase intent

In that vein, you can close your anticipated business gaps by predicting who will buy your product and who won't. Using behavioral cues that signal the seriousness of a shopper will help you spend more time, energy, and resources on customers who are more likely to convert. For example, if your company offers a free trial for business software, try targeted marketing campaigns aimed at those who signed up with a business email address rather than those who signed up with a personal or "junk" address. By using predictive analytics to determine what behaviors correlate with purchases, you can aim your marketing efforts accordingly.

4. Getting pricing right:

Predictive analytics can also reveal pricing trends or price elasticity, which is one of the most important keys to success. Combining big data market behavior with your customers' reaction to various promotions can help you tweak your pricing to maximize gains throughout the year so that you aren't leaving money on the table.

5. Internal forecasting:

Last, but certainly not least, you can also use predictive analytics to help set your annual business goals. By forecasting demand, your revenue run rate, and periods of growth, you can prepare for and strive toward measurable outcomes that will catapult your company forward. This type of forecasting also helps you understand if your goals are too high or too low so your team understands the impact of their work.

See, we told you that you could see the future. Big data is the future ... and so are the insights it provides.